Senior Product Manager - Data Lakehouse (f/m/d)

Trusted Shops SE (DE)

Source: RecruiteeLocation: Germany onlyPublished: Sep 04, 2026Confirmed active: Sep 19, 2026
Full-timeFreelance / Contract40 hrs/week

Key points from the posting

Tech stack
Data LakehouseAPIsMCPBI
Seniority:
Senior

Read out of the job posting automatically

Our assessment

  • Our reading of the full posting text confirms it: fully remote.
  • 12 more open roles from this employer in our index. 5 of them fully remote.

This section only: calculated automatically by nomado24, from our own job index and our own reading of the posting text. Not stated by the employer.

Job description

Trusted Shops creates digital trust between people, businesses, and AI agents, with one clear goal: becoming the #1 Community of Trust. Every day, we help businesses build trust online and empower consumers to make confident decisions in an increasingly digital world.

As our products, reporting capabilities, and AI-driven use cases continue to grow, the company increasingly needs prepared, standardized data products – the data basis for self-service reporting, APIs (Metrics-as-a-Service), and AI-driven access via MCP or Chat interfaces. You and your team will own the whole journey from raw data to documented, trustworthy data products that people and machines can actually use.

To strengthen our Data Services department, we are looking for a

Senior Product Manager - Data Lakehouse (m/f/d)

(Hybrid in Cologne or remote in Berlin / Full-time / Permanent contract)

Responsibilities

  • You own the product portfolio and roadmap for the domain, driving the shift from reactive requests ("build the metric asked for") to proactive, reusable metric standards.
  • You run data products end-to-end. You know your consumers, treat them as customers, and track whether they actually trust and use what you ship.
  • Together with your team, you define the semantic layer: metric and dimension definitions, metadata, and documentation that make a data product clear to people working in BI tools and reliable for AI agents.
  • You provide metrics-as-a-service. Your team exposes metrics through an API that product engineering teams integrate directly into their own products.
  • You are the point of contact for internal consumers and product teams: you set expectations, explain trade-offs, and say no when needed. You align shared standards and dimensions with the Finance Data Domain team and work with the Data Platform team as your service provider.
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